The use of separate luma and chroma image sensors, such as cameras, to capture a high quality image is known. In particular, the use of separate luma and chroma image sensors can produce a combined higher quality image when compared to what can be achieved by a single image sensor.
Implementing an imaging system using separate luma and chroma image sensors involves dealing with alignment and disparity issues that result from separate image sensors. Specifically, known approaches deal with epipolar geometry alignment by generating a transform that can be applied to the luma and chroma data obtained by the separate image sensors. Known approaches deal with stereo disparity compensation using a software-based approach. The software-based approach extrapolates from the image data obtained by the luma and chroma image sensors. For example, one approach is to perform edge detection in the image data to determine what disparity compensation to apply. The following review several methods according to the software-based approach: (1) D. Scharstein and R. Szeliski, A taxonomy and evaluation of dense two-frame stereo compensation algorithms, International Journal of Computer Vision, 47(1/2/3):7-42, Apr.-Jun. 2002; (2) Microsoft Research Technical Report MSR-TR-2001-81, November 2001, each of which is incorporated by reference herein in its entirety.